{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Long-Horizon Forecasting with NHITS"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Long-horizon forecasting is challenging because of the *volatility* of the predictions and the *computational complexity*. To solve this problem we created the [NHITS](https://arxiv.org/abs/2201.12886) model and made the code available [NeuralForecast library](https://nixtla.github.io/neuralforecast/models.nhits.html). `NHITS` specializes its partial outputs in the different frequencies of the time series through hierarchical interpolation and multi-rate input\n",
    "processing. \n",
    "\n",
    "In this notebook we show how to use `NHITS` on the [ETTm2](https://github.com/zhouhaoyi/ETDataset) benchmark dataset. This data set includes data points for 2 Electricity Transformers at 2 stations, including load, oil temperature.\n",
    "\n",
    "We will show you how to load data, train, and perform automatic hyperparameter tuning, **to achieve SoTA performance**, outperforming even the latest Transformer architectures for a fraction of their computational cost (50x faster)."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can run these experiments using GPU with Google Colab.\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/Nixtla/neuralforecast/blob/main/nbs/examples/LongHorizon_with_NHITS.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Installing NeuralForecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "!pip install neuralforecast datasetsforecast"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Load ETTm2 Data\n",
    "\n",
    "The `LongHorizon` class will automatically download the complete ETTm2 dataset and process it.\n",
    "\n",
    "It return three Dataframes: `Y_df` contains the values for the target variables, `X_df` contains exogenous calendar features and `S_df` contains static features for each time-series (none for ETTm2). For this example we will only use `Y_df`.\n",
    "\n",
    "If you want to use your own data just replace `Y_df`. Be sure to use a long format and have a simmilar structure than our data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique_id</th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HUFL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>-0.041413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HUFL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>-0.185467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57600</th>\n",
       "      <td>HULL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>0.040104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57601</th>\n",
       "      <td>HULL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>-0.214450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115200</th>\n",
       "      <td>LUFL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>0.695804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115201</th>\n",
       "      <td>LUFL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>0.434685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172800</th>\n",
       "      <td>LULL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>0.434430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172801</th>\n",
       "      <td>LULL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>0.428168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230400</th>\n",
       "      <td>MUFL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>-0.599211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230401</th>\n",
       "      <td>MUFL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>-0.658068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288000</th>\n",
       "      <td>MULL</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>-0.393536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288001</th>\n",
       "      <td>MULL</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>-0.659338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345600</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>1.018032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345601</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 00:15:00</td>\n",
       "      <td>0.980124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       unique_id                  ds         y\n",
       "0           HUFL 2016-07-01 00:00:00 -0.041413\n",
       "1           HUFL 2016-07-01 00:15:00 -0.185467\n",
       "57600       HULL 2016-07-01 00:00:00  0.040104\n",
       "57601       HULL 2016-07-01 00:15:00 -0.214450\n",
       "115200      LUFL 2016-07-01 00:00:00  0.695804\n",
       "115201      LUFL 2016-07-01 00:15:00  0.434685\n",
       "172800      LULL 2016-07-01 00:00:00  0.434430\n",
       "172801      LULL 2016-07-01 00:15:00  0.428168\n",
       "230400      MUFL 2016-07-01 00:00:00 -0.599211\n",
       "230401      MUFL 2016-07-01 00:15:00 -0.658068\n",
       "288000      MULL 2016-07-01 00:00:00 -0.393536\n",
       "288001      MULL 2016-07-01 00:15:00 -0.659338\n",
       "345600        OT 2016-07-01 00:00:00  1.018032\n",
       "345601        OT 2016-07-01 00:15:00  0.980124"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from datasetsforecast.long_horizon import LongHorizon\n",
    "\n",
    "# Change this to your own data to try the model\n",
    "Y_df, _, _ = LongHorizon.load(directory='./', group='ETTm2')\n",
    "Y_df['ds'] = pd.to_datetime(Y_df['ds'])\n",
    "\n",
    "# For this excercise we are going to take 20% of the DataSet\n",
    "n_time = len(Y_df.ds.unique())\n",
    "val_size = int(.2 * n_time)\n",
    "test_size = int(.2 * n_time)\n",
    "\n",
    "Y_df.groupby('unique_id').head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# We are going to plot the temperature of the transformer \n",
    "# and marking the validation and train splits\n",
    "u_id = 'HUFL'\n",
    "x_plot = pd.to_datetime(Y_df[Y_df.unique_id==u_id].ds)\n",
    "y_plot = Y_df[Y_df.unique_id==u_id].y.values\n",
    "\n",
    "x_val = x_plot[n_time - val_size - test_size]\n",
    "x_test = x_plot[n_time - test_size]\n",
    "\n",
    "fig = plt.figure(figsize=(10, 5))\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.plot(x_plot, y_plot)\n",
    "plt.xlabel('Date', fontsize=17)\n",
    "plt.ylabel('HUFL [15 min temperature]', fontsize=17)\n",
    "\n",
    "plt.axvline(x_val, color='black', linestyle='-.')\n",
    "plt.axvline(x_test, color='black', linestyle='-.')\n",
    "plt.text(x_val, 5, '  Validation', fontsize=12)\n",
    "plt.text(x_test, 5, '  Test', fontsize=12)\n",
    "\n",
    "plt.grid()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Hyperparameter selection and forecasting\n",
    "\n",
    "The `AutoNHITS` class will automatically perform hyperparamter tunning using [Tune library](https://docs.ray.io/en/latest/tune/index.html), exploring a user-defined or default search space. Models are selected based on the error on a validation set and the best model is then stored and used during inference. \n",
    "\n",
    "The `AutoNHITS.default_config` attribute contains a suggested hyperparameter space. Here, we specify a different search space following the paper's hyperparameters. Notice that *1000 Stochastic Gradient Steps* are enough to achieve SoTA performance. Feel free to play around with this space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ray import tune\n",
    "from neuralforecast.auto import AutoNHITS\n",
    "from neuralforecast.core import NeuralForecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "horizon = 96 # 24hrs = 4 * 15 min.\n",
    "\n",
    "# Use your own config or AutoNHITS.default_config\n",
    "nhits_config = {\n",
    "       \"learning_rate\": tune.choice([1e-3]),                                     # Initial Learning rate\n",
    "       \"max_steps\": tune.choice([1000]),                                         # Number of SGD steps\n",
    "       \"input_size\": tune.choice([5 * horizon]),                                 # input_size = multiplier * horizon\n",
    "       \"batch_size\": tune.choice([7]),                                           # Number of series in windows\n",
    "       \"windows_batch_size\": tune.choice([256]),                                 # Number of windows in batch\n",
    "       \"n_pool_kernel_size\": tune.choice([[2, 2, 2], [16, 8, 1]]),               # MaxPool's Kernelsize\n",
    "       \"n_freq_downsample\": tune.choice([[168, 24, 1], [24, 12, 1], [1, 1, 1]]), # Interpolation expressivity ratios\n",
    "       \"activation\": tune.choice(['ReLU']),                                      # Type of non-linear activation\n",
    "       \"n_blocks\":  tune.choice([[1, 1, 1]]),                                    # Blocks per each 3 stacks\n",
    "       \"mlp_units\":  tune.choice([[[512, 512], [512, 512], [512, 512]]]),        # 2 512-Layers per block for each stack\n",
    "       \"interpolation_mode\": tune.choice(['linear']),                            # Type of multi-step interpolation\n",
    "       \"val_check_steps\": tune.choice([100]),                                    # Compute validation every 100 epochs\n",
    "       \"random_seed\": tune.randint(1, 10),\n",
    "    }"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{.callout-tip}\n",
    "Refer to https://docs.ray.io/en/latest/tune/index.html for more information on the different space options, such as lists and continous intervals.m\n",
    ":::"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To instantiate `AutoNHITS` you need to define:\n",
    "\n",
    "* `h`: forecasting horizon\n",
    "* `loss`: training loss. Use the `DistributionLoss` to produce probabilistic forecasts.\n",
    "* `config`: hyperparameter search space. If `None`, the `AutoNHITS` class will use a pre-defined suggested hyperparameter space.\n",
    "* `num_samples`: number of configurations explored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = [AutoNHITS(h=horizon,\n",
    "                    config=nhits_config, \n",
    "                    num_samples=5)]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit the model by instantiating a `NeuralForecast` object with the following required parameters:\n",
    "\n",
    "* `models`: a list of models.\n",
    "\n",
    "* `freq`: a string indicating the frequency of the data. (See [panda's available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases).)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `cross_validation` method allows you to simulate multiple historic forecasts, greatly simplifying pipelines by replacing for loops with `fit` and `predict` methods.\n",
    "\n",
    "With time series data, cross validation is done by defining a sliding window across the historical data and predicting the period following it. This form of cross validation allows us to arrive at a better estimation of our model’s predictive abilities across a wider range of temporal instances while also keeping the data in the training set contiguous as is required by our models.\n",
    "\n",
    "The `cross_validation` method will use the validation set for hyperparameter selection, and will then produce the forecasts for the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "nf = NeuralForecast(\n",
    "    models=models,\n",
    "    freq='15min')\n",
    "\n",
    "Y_hat_df = nf.cross_validation(df=Y_df, val_size=val_size,\n",
    "                               test_size=test_size, n_windows=None)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Evaluate Results\n",
    "\n",
    "The `AutoNHITS` class contains a `results` tune attribute that stores information of each configuration explored. It contains the validation loss and best validation hyperparameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'learning_rate': 0.001,\n",
       " 'max_steps': 1000,\n",
       " 'input_size': 480,\n",
       " 'batch_size': 7,\n",
       " 'windows_batch_size': 256,\n",
       " 'n_pool_kernel_size': [2, 2, 2],\n",
       " 'n_freq_downsample': [24, 12, 1],\n",
       " 'activation': 'ReLU',\n",
       " 'n_blocks': [1, 1, 1],\n",
       " 'mlp_units': [[512, 512], [512, 512], [512, 512]],\n",
       " 'interpolation_mode': 'linear',\n",
       " 'val_check_steps': 100,\n",
       " 'random_seed': 8,\n",
       " 'h': 96,\n",
       " 'loss': MAE(),\n",
       " 'valid_loss': MAE()}"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nf.models[0].results.get_best_result().config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parsed results\n",
      "2. y_true.shape (n_series, n_windows, n_time_out):\t (7, 11425, 96)\n",
      "2. y_hat.shape  (n_series, n_windows, n_time_out):\t (7, 11425, 96)\n"
     ]
    }
   ],
   "source": [
    "y_true = Y_hat_df.y.values\n",
    "y_hat = Y_hat_df['AutoNHITS'].values\n",
    "\n",
    "n_series = len(Y_df.unique_id.unique())\n",
    "\n",
    "y_true = y_true.reshape(n_series, -1, horizon)\n",
    "y_hat = y_hat.reshape(n_series, -1, horizon)\n",
    "\n",
    "print('Parsed results')\n",
    "print('2. y_true.shape (n_series, n_windows, n_time_out):\\t', y_true.shape)\n",
    "print('2. y_hat.shape  (n_series, n_windows, n_time_out):\\t', y_hat.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1100 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=3, ncols=1, figsize=(10, 11))\n",
    "fig.tight_layout()\n",
    "\n",
    "series = ['HUFL','HULL','LUFL','LULL','MUFL','MULL','OT']\n",
    "series_idx = 3\n",
    "\n",
    "for idx, w_idx in enumerate([200, 300, 400]):\n",
    "  axs[idx].plot(y_true[series_idx, w_idx,:],label='True')\n",
    "  axs[idx].plot(y_hat[series_idx, w_idx,:],label='Forecast')\n",
    "  axs[idx].grid()\n",
    "  axs[idx].set_ylabel(series[series_idx]+f' window {w_idx}', \n",
    "                      fontsize=17)\n",
    "  if idx==2:\n",
    "    axs[idx].set_xlabel('Forecast Horizon', fontsize=17)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we compute the test errors for the two metrics of interest:\n",
    "\n",
    "$\\qquad MAE = \\frac{1}{Windows * Horizon} \\sum_{\\tau} |y_{\\tau} - \\hat{y}_{\\tau}| \\qquad$ and $\\qquad MSE = \\frac{1}{Windows * Horizon} \\sum_{\\tau} (y_{\\tau} - \\hat{y}_{\\tau})^{2} \\qquad$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE:  0.24862242128243706\n",
      "MSE:  0.17257850996828134\n"
     ]
    }
   ],
   "source": [
    "from neuralforecast.losses.numpy import mae, mse\n",
    "\n",
    "print('MAE: ', mae(y_hat, y_true))\n",
    "print('MSE: ', mse(y_hat, y_true))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For reference we can check the performance when compared\n",
    "to previous 'state-of-the-art' long-horizon Transformer-based forecasting methods from the [NHITS paper](https://arxiv.org/abs/2201.12886). To recover or improve the paper results try setting `hyperopt_max_evals=30` in [Hyperparameter Tuning](#cell-4).\n",
    "\n",
    "Mean Absolute Error (MAE):\n",
    "\n",
    "| Horizon   | NHITS        | AutoFormer | InFormer | ARIMA \n",
    "|---        |---           |---         |---       |---\n",
    "|  96       |  **0.249**   |   0.339    |  0.453   | 0.301 \n",
    "|  192      |  0.305       |   0.340    |  0.563   | 0.345 \n",
    "|  336      |  0.346       |   0.372    |  0.887   | 0.386 \n",
    "|  720      |  0.426       |   0.419    |  1.388   | 0.445 \n",
    "\n",
    "Mean Squared Error (MSE):\n",
    "\n",
    "| Horizon   | NHITS        | AutoFormer | InFormer | ARIMA \n",
    "|---        |---           |---         |---       |---\n",
    "|  96       |  **0.173**   |   0.255    |  0.365   | 0.225 \n",
    "|  192      |  0.245       |   0.281    |  0.533   | 0.298 \n",
    "|  336      |  0.295       |   0.339    |  1.363   | 0.370 \n",
    "|  720      |  0.401       |   0.422    |  3.379   | 0.478 "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "[Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza, Max Mergenthaler-Canseco, Artur Dubrawski (2021). NHITS: Neural Hierarchical Interpolation for Time Series Forecasting. Accepted at AAAI 2023.](https://arxiv.org/abs/2201.12886)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
